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Can the Rockchip RK3588 / RK3588S (8 GB) run Zamba2 2.7B Instruct?

18Basic quality (D) · 18 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking.

Yes, it runs well

Runs well. At Q3_K_M it needs about 2.8 GB of 6.4 GB usable, with an estimated speed of 16.8 tok/s.

Best quant
Q3_K_M
Generation speed
16.8 tok/s
Prompt processing
45.1 tok/s
First token (1K prompt)
22.7 s
Largest safe context
4K

Best app to run it on the Rockchip RK3588 / RK3588S (8 GB)

On Linux on ARM boards

Docker Model Runner

Command line + local API · runs on llama.cpp, vLLM

  • Handy if you already work in Docker.
docker model run hf.co/Zyphra/Zamba2-2.7B-instruct

How we choose: the files published for this model, your operating system and GPU, whether it fits fully in memory, and published speed tests (MLX vs llama.cpp on Apple silicon, vLLM vs llama.cpp vs Ollama on NVIDIA). Details.

Download Zamba2 2.7B Instruct

Original weights · Hugging Face

Full-precision files from Zyphra, for fine-tuning, vLLM, Transformers.

huggingface.co/Zyphra/Zamba2-2.7B-instruct (opens in a new tab)

No sign-in needed.

Links checked 2 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 18Basic quality (D) · 18 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q3_K_M, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Runs well
How well it runs on the Rockchip RK3588 / RK3588S (8 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.8.3 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; fewer when it goes past that limit.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.9.7 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.10.1 / 15
Match score53.1 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the Rockchip RK3588 / RK3588S (8 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 2.6 GB 6.4 GB 21.3 tok/s Runs well 15Basic quality (D) · 15 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 2.8 GB 6.4 GB 16.8 tok/s Runs well 18Basic quality (D) · 18 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 3.1 GB 6.4 GB 13.0 tok/s Runs well 20Basic quality (D) · 20 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 3.4 GB 6.4 GB 10.7 tok/s Runs well 21Basic quality (D) · 21 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 3.7 GB 6.4 GB 9.0 tok/s Slow 21Basic quality (D) · 21 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 4.3 GB 6.4 GB 6.6 tok/s Slow 22Basic quality (D) · 22 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 6.8 GB 6.4 GB 2.6 tok/s Very slowover memory limit 22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 38/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)

Memory figures assume 4K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Quick answers

How much memory does Zamba2 2.7B Instruct need on the Rockchip RK3588 / RK3588S 8GB?

At Q3_K_M it needs about 2.8 GB. The Rockchip RK3588 / RK3588S 8GB has 6.4 GB usable.

How fast is Zamba2 2.7B Instruct on the Rockchip RK3588 / RK3588S 8GB?

About 16.8 tok/s at Q3_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of Zamba2 2.7B Instruct should I use on the Rockchip RK3588 / RK3588S 8GB?

Q3_K_M. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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